Adaptive resource reservoir development

ABSTRACT

A plurality of development scenarios is determined. At least a first well is drilled at a first location and trajectory that are common to the plurality of development scenarios. A result of the at least one first well is assessed. A first subset of development scenarios is selected from the plurality of development scenarios based at least on the result of the first well. A first sequence of subsequent wells, including at least one well, are drilled at a first sequence of subsequent locations and trajectories that are common to the first subset of development scenarios.

BACKGROUND

The present invention relates to subterranean fluid resources, and, moreparticularly, to resource field development planning and the like.

The current practice in oil companies consists of designing a singledeterministic reservoir development plan, which describes a singlelocation and trajectory for each one of the wells to be drilled. Thiscan be achieved in many different ways: by using an expert's judgmentand/or optimization algorithms; by considering a single best guessscenario and/or different scenarios to account for uncertainty.Sometimes, the deterministic plan is selected from a set of potentialplans, based on comparing a statistical average of performance metricsfor each plan in a variety of geological realizations. In any of thesecases, the current practice still has as its goal to determine a singledeterministic plan. The argument supporting this practice is that thereis only one “ground truth” and, therefore, there is only one plan thatcan be implemented.

SUMMARY

Principles of the invention provide techniques for adaptive resourcefield development, in which a multi-branch decision tree is providedthat incorporates multiple development plans corresponding to multiplepotential field realizations. In one aspect, an exemplary methodincludes determining a plurality of development scenarios; drilling atleast a first well at a first location and trajectory that are common tothe plurality of development scenarios; assessing a result of the atleast one first well; and drilling a first sequence of subsequent wellsat a first sequence of subsequent locations and trajectories that arecommon to a first subset of development scenarios, wherein the firstsubset includes at least one development scenario that is selected fromthe plurality of development scenarios based at least on the result ofthe first well, wherein the first sequence of subsequent wells includesat least one well.

In another aspect, an exemplary method includes drilling a firstappraisal well at a first appraisal location and trajectory; drilling afirst sequence of production wells at a first sequence of productionlocations and trajectories selected based on results of the firstappraisal well; drilling a second appraisal well at a second appraisallocation and trajectory; and drilling a second sequence of productionwells at a second sequence of production locations and trajectoriesbased on results of the first and second appraisal wells. The firstappraisal location and trajectory are determined a priori while at leastthe first sequence of production locations and trajectories and thesecond sequence of production locations and trajectories are selectedlater from a plurality of development scenarios determined a priori.

Other embodiments of the invention provide a computer program productthat includes a computer readable storage medium, which embodiescomputer executable instructions which when executed by a computer causethe computer to facilitate receiving, at a technological tree (TT)builder module, a set of development scenarios, each developmentscenario comprising a combination of well locations and trajectoriescorresponding to appraisal wells and production wells; building, in thetechnological tree builder module, a technological tree based on the setof development scenarios; receiving, at the development manualproduction module, a set of geological realizations; modeling, in thedevelopment manual production module, performance metrics for each ofthe development scenarios for each of the set of geologicalrealizations; based on the TT and modeled performance metrics,identifying decisions at each internal node of the TT; and based on theTT and decisions to be made at each its node, producing a pre-calculatedresource field development manual in the development manual productionmodule.

Other embodiments of the invention provide an apparatus that includes amemory and at least one processor. The processor is operative tofacilitate receiving, at a technological tree builder module, a set ofdevelopment scenarios, each development scenario comprising acombination of well locations and trajectories corresponding toappraisal wells and production wells; building, in the technologicaltree builder module, a technological tree based on the set ofdevelopment scenarios; receiving, at the development manual productionmodule, a set of geological realizations; modeling, in the developmentmanual production module, performance metrics for each of thedevelopment scenarios for each of the set of geological realizations;based on the TT and modeled performance metrics, identifying decisionsat each internal node of the TT; and based on the TT and decisions to bemade at each of its internal nodes, producing a pre-calculated resourcefield development manual in the development manual production module.

As used herein, “facilitating” an action includes performing the action,making the action easier, helping to carry the action out, or causingthe action to be performed. Thus, by way of example and not limitation,instructions executing on one processor might facilitate an actioncarried out by instructions executing on a remote processor, by sendingappropriate data or commands to cause or aid the action to be performed.For the avoidance of doubt, where an actor facilitates an action byother than performing the action, the action is nevertheless performedby some entity or combination of entities.

One or more embodiments of the invention or elements thereof can beimplemented in the form of a computer program product including acomputer readable storage medium with computer usable program code forperforming the method steps indicated. Furthermore, one or moreembodiments of the invention or elements thereof can be implemented inthe form of a system (or apparatus) including a memory, and at least oneprocessor that is coupled to the memory and operative to performexemplary method steps. Yet further, in another aspect, one or moreembodiments of the invention or elements thereof can be implemented inthe form of means for carrying out one or more of the method stepsdescribed herein; the means can include (i) hardware module(s), (ii)software module(s) stored in a computer readable storage medium (ormultiple such media) and implemented on a hardware processor, or (iii) acombination of (i) and (ii); any of (i)-(iii) implement the specifictechniques set forth herein.

Techniques of the present invention can provide substantial beneficialtechnical effects. For example, one or more embodiments may provide oneor more of the following advantages:

Enhanced productivity of newly developed resource fields by comparisonto conventional development practices.

Reduced drilling costs per unit of cumulative resource production.

Rapid adaptation of resource field development plans in response toevolving information on geological parameters.

Robust decision-making that incorporates opportunities to deal withuncertainty.

These and other features and advantages of the present invention willbecome apparent from the following detailed description of illustrativeembodiments thereof, which is to be read in connection with theaccompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a cloud computing environment according to an embodimentof the present invention;

FIG. 2 depicts abstraction model layers according to an embodiment ofthe present invention;

FIG. 3 shows in schematic form a plurality of reservoir developmentscenarios incorporating well locations and trajectories;

FIG. 4 depicts a technological tree for an adaptive reservoirdevelopment plan that accounts for the various development scenariosshown in FIG. 3, according to embodiments of the invention;

FIG. 5 shows a flowchart for pre-calculating a reservoir developmentmanual based on a set of geological realizations, on an economicalmodel, and on a set of development scenarios;

FIG. 6 shows a flowchart for building a technological tree (FIG. 4 showsan example of a technological tree built according to the process ofFIG. 6), according to embodiments of the invention;

FIG. 7 depicts in tabular form a reservoir development manual calculatedaccording to FIG. 5;

FIG. 8 shows graphically relationships between values of an uncertainparameter and values of an estimated performance metric for differentdevelopment scenarios;

FIG. 9 shows in tabular form the data of FIG. 8 along with thedevelopment scenarios that maximize the performance metric for somevalues of the uncertain parameter;

FIG. 10 shows in tabular form a step of identifying an optimaldevelopment scenario for a plurality of geological realizations;

FIG. 11 shows a flowchart for developing a resource field by an adaptivereservoir development plan, according to embodiments of the invention;and

FIG. 12 depicts a computer system configurable to implement embodimentsof the invention.

DETAILED DESCRIPTION

The subject matter of the instant application will be described withreference to illustrative embodiments. Numerous modifications can bemade to these embodiments and the results will still come within thescope of the invention. No limitations with respect to the specificembodiments described herein are intended or should be inferred.

Although a particular embodiment of the invention is described in detailherein with reference to the development of oil fields, it is to beunderstood that the invention is equally applicable to othersubterranean fluid resources, e.g., natural gas, fresh water, orgeothermal steam.

It is to be understood that although this disclosure includes a detaileddescription on cloud computing, implementation of the teachings recitedherein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g., networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported, providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure that includes anetwork of interconnected nodes.

Referring now to FIG. 1, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 includes one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 1 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 2, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 1) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 2 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may include applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and adaptive resource field developmentplanning 96.

As discussed above, conventional techniques for oil reservoirdevelopment planning involve designing a single deterministic reservoirdevelopment plan with a single location/trajectory (though possiblyincluding multilateral completions) for each one of the wells to bedrilled. Sometimes, the single plan is arrived at by comparing aplurality of potential plans based on calculation of some commonperformance metric for each of the plans. For example, cumulative oilproduction may be calculated for each plan. However, accuracy in suchcalculations requires knowledge of subsurface structures (a geologicalmodel of the oil field) that is, in general, not available before wellshave been drilled. Accordingly, it is usually not possible to accuratelycalculate the common performance metric. This raises the question how toselect among the plurality of potential drilling plans.

One known solution is to calculate a performance metric for each one ofa set “D” of potential drilling plans, across a set “M” of possiblegeological realizations or reservoir models. The result of suchcalculation is a D×M matrix of possible performance metrics. The columnsof the matrix (each column corresponding to a drilling plan) can then becompared. For example, the columns can be compared on the basis of somestatistical averaging of the values within each column. Another optionmight be to compare the magnitudes of the columns. In any case, based onthe a priori comparison, a single deterministic reservoir developmentplan is selected to yield an optimal value of the comparison.

According to conventional methods, the set M can be limited by drillinga priori (before determining a single deterministic development plan)one or more “appraisal wells,” which are wells drilled for the purposeof taking measurements before drilling production wells for the purposeof extracting fluid resources. Using the measurements from appraisalwells, it is possible to simulate subsurface structures that might beconsistent with those measurements. Such simulations necessarily areprobabilistic and yield a relatively large set M for each measurement;multiple measurements can reduce the scale of the set M. However, thetight schedule of reservoir development typically does not give anopportunity for precise measurements at the outset of drilling. Thedevelopment team needs to drill production wells as a first priority,and perform additional research only occasionally. The result isextensive geological uncertainty due to limited knowledge about thesubsurface, so that an initially optimal drilling plan (the singledeterministic reservoir development plan arrived at by conventionalmethods) may no longer be optimal as more wells are drilled andadditional knowledge about the reservoir becomes available.

Thus, it would be advantageous to adapt a reservoir development planbased on evolving information, according to embodiments of theinvention. Unfortunately, the conventional approach to evaluating wellmeasurements is to design an updated or augmented set of developmentscenarios (that take into account the production wells that have beendrilled so far) and entirely recalculate a simulation of subsurfacestructures for each new set of measurements. This conventional approachis usually computationally intensive and time-consuming, and does notfit within the typically rapid production drilling schedule so as topermit meaningful adaptation of a pre-determined drilling plan. Thus, itwould be advantageous to adapt a reservoir development plan based on newinformation, in a rapid manner that does not require intensiverecalculation associated with new measurements. Embodiments of theinvention provide for such rapid adaptation.

More particularly, embodiments of the invention advantageously allow fordevelopment plans to be defined incorporating some degree of flexibilitythat allows for adaptation in response to evolving information ongeological realizations, as opposed to current practices based on adeterministic plan which does not provide flexibility for locationsand/or trajectories of new wells despite uncertainty in fieldparameters. Based on the information provided by ongoing fieldexploration during drilling, the development team can adapt the drillingscenario dynamically. The invention provides a fully automatic tool thattells the operator what to drill based on the results obtained fromappraisal wells that the operator enters into the system.

Although the present application describes primarily a reservoirdevelopment application based on oil production by water flooding inwhich the reservoir contains oil and water, but there is no gas, oneskilled in the art will understand that inventive techniques may beutilized in other contexts, such as oil production through othertechniques, gas production, water well drilling, etc.

Embodiments of the invention provide for efficient and adaptivedevelopment of undeveloped oil fields (also known as “greenfields”).However, embodiments of the invention also are applicable touncharacterized or only partly characterized portions of previouslydeveloped fields (brownfields). The invention can be applied in order toadaptively select an optimized drilling scenario by alternate drillingof production and appraisal (pilot) wells. An appraisal well is anon-production well that delivers additional local knowledge (reducesuncertainty on geological parameters of the field), which knowledgemight not be relevant for other regions of the field. Drilling anappraisal well incurs cost and delays drilling of production wells. Bydrilling fewer appraisal wells at the beginning of the developmentprocess, we have a quick start of the drilling of production wellswhich, in turn, helps to reduce the time needed to returnpre-development investments. On the other hand, having at least a fewappraisal wells tends to yield better production well placement andhigher overall field performance than having no appraisal wells. Anaspect of the invention is that appraisal wells can be drilledinterspersed with production wells and using the same drillingmachinery. This approach saves on cost while permitting rapid adaptationof the reservoir development plan. Commonly found examples of reservoirdevelopment plan adaptations are adjustments of the number of productionwells and of their locations (i.e., the adjustment of well density).Embodiments of the invention provide drilling schedules of productionand appraisal wells for a multitude of technologically achievableproduction well arrangements with predefined well locations and depths.The schedules are generated so that at each stage the expected meanperformance metric is maximized (very often an economic metric, e.g.,net present value, is considered, but production metrics, e.g.,cumulative oil production, can also be used).

Referring now to FIG. 3, the invention contemplates in this examplevarious reservoir development scenarios DS1, DS2 and DS3 undergeological uncertainties. Each development scenario (DS) includes a listof activities to be performed during the development of a reservoir (forexample, installation of production facilities and infrastructure,drilling of production wells of specified depths at predefinedlocations, drilling and obtaining information from appraisal wells,obtaining information from previously drilled production wells). A DScan specify complex temporal dependencies between activities (forexample, drilling of two appraisal wells, one immediately after anothermay be prohibited). Some activities of a DS must be completed fully (forexample, drilling of production wells), and some other activities may betotally ignored during the implementation of a scenario (for example, aDS may allow for drilling of fewer number of appraisal wells compared tothe maximum number of appraisal wells allowed in the scenario). Animplementation of a DS is a process of performing activities specifiedin the DS taking into account their dependencies. A DS is fullyimplemented when all activities of a DS that must be completed fullyhave been performed. Depending on geological parameters of the field(which are not known with certainty even after all the appraisal wellshave been drilled and evaluated), different DSs may be optimal fordeveloping the field. Embodiments of the invention help the operator toadapt the development of a reservoir by selecting among the various apriori DSs, based on additional information about field parameters thatis obtained during development according to the invention.

Exemplary actions under a DS include the following: Drill an appraisalwell and analyze the results to reduce the reservoir uncertainty byeliminating geological realizations that are not consistent with theappraisal results. Choose a location and trajectory of a productionwell, among all technologically allowed options, and drill it. Finishthe drilling of wells for the reservoir.

For example, DS1 in FIG. 3 requires the drilling of three productionwells W1, W2 and W4. DS2 requires drilling three production wells W1, W3and W4. DS3 requires drilling only two production wells: W2 and W3. Eachwell is characterized by a location (e.g., GPS coordinates of thewellhead) and by a trajectory (i.e., a depth, an azimuth, and ahorizontal distance that could be zero). For simplicity, FIG. 3 showsonly a longitudinal coordinate of each well in the moving direction ofthe drilling machinery.

The mutual underground arrangement of horizontal production wells isrestricted by the following technological limitations: The separationbetween the closest wells should lie in some predefined range. The wellscould be drilled out of order, but the number of wells drilledout-of-order might be limited. The first limitation is taken intoaccount by the appropriate choice of well patterns.

Although the location and trajectory of each potential production wellhas been pre-determined based on the pre-development data from fieldsensors, including the initial appraisal well(s), the differentdevelopment scenarios lay out distinct sequences of locations andtrajectories that correspond to distinct sequences of production welldrilling. Which sequences are accomplished in which order can bedetermined according to embodiments of the invention, as furtherdescribed with reference to FIGS. 4-7 and 11.

Embodiments of the invention comprise two parts. The first part is amethod that creates a pre-calculated manual to be used during thedevelopment of a reservoir. The second part is a method that utilizesthis pre-calculated development manual to dynamically adapt adevelopment plan in response to discovered information about geologicalparameters of the field under development.

FIGS. 4-6 depict, as a first part of the invention, how thepre-calculated development manual is built according to the followingthree-step procedure:

1. Representation of all possible transitions between implementationschedules of development scenarios in a form of a hierarchical structure(technological tree 400, shown in FIG. 4). The tree 400 has leaves orterminal nodes 402, nodes where transition between development scenarioshappen (internal nodes) 403 and 404, and a root 406. Each leaf 402corresponds to one development scenario. After building TT, we calculateperformance metrics for possible geological models in each leafaccording to the path from the root to the leaf taking into account theappraisal wells. Thus, the leaves 402 correspond either to completion ofa DS or to a halt of drilling due to negative evaluation of performancemetrics for any allowed DS.

Each internal node 404 (“P”) corresponds to an immediate measurementevent (e.g., get information from appraisal well), which produces aresult that can be used to eliminate one or more of the leaves 402—i.e.a result that is consistent with only some of the geologicalrealizations in the set M. We will denote these nodes “P” nodes. Forexample, consider a set of reservoir models where each model correspondsto the value of a given uncertain parameter, for example, some averagevalue of the rock porosity in the reservoir, which, in this example, maytake values in the interval [0.1, 0.2]. Different porosity values wouldimply different physics and, in turn, different fluid production. Inthis simple example, let's say that the interval [0.1, 0.15] correspondsto a reservoir with relatively LOW average porosity and the interval[0.15, 0.2] to a reservoir with relatively HIGH porosity. Notice thatparticular measurements and interpretation techniques (i.e., wellporosity logs) give information about that specific property (i.e.,porosity) in an area of the reservoir close to where the measurementsare taken, i.e. close to the appraisal well. Additionally, there isuncertainty in these measurements. Taking all this into consideration,one set of measurements does not allow to exactly say that the averageporosity in the reservoir is, e.g., 0.12. Rather, limited measurementspermit an estimate that the reservoir has relatively LOW averageporosity (i.e., the porosity values close to the measurements may bearound 0.12; however, in the rest of the reservoir the value could bedifferent and, for some other reasons related to other measurements orinformation available, significant variation of porosity in thereservoir is not expected, so on average there are values of porosity inthe interval [0.1, 0.15] that yield acceptable predictions of fluidflow, exemplary performance metric, for a particular subset ofdevelopment scenarios). Thus, “P”-node would imply “drill appraisal welland choose next action based on the outcomes of previous appraisals aswell as the just obtained appraisal.”

Between the “P” nodes 404 are production well nodes 403 (“W1”, “W2”,“W3” and “W4” in FIG. 4) that correspond to drilling of the variouswells described with reference to the development scenarios of FIG. 3.We will denote these nodes as action nodes or “W” nodes. Data fromproduction wells (e.g., flow data) is obtained only with some lag time,which, in some cases, is not economical to wait. Accordingly, “W”-nodewould imply “drill production well and choose the next action based onthe outcomes of previous appraisals.”

2. Evaluation of expected value of performance metric for everyimplementation of each development scenario in each geologicalrealization (method 500, FIG. 5).

3. Identification of decisions at each point of transition betweenimplementation schedules by means of backward induction approach(further discussed below with reference to FIGS. 5 and 8-10).

The technological tree 400 represents all the possible actions that theuser may perform (i.e., “P”, which denotes drilling a pilot/appraisalwell; “W1”, “W2”, “W3” and “W4”, which denote drilling production wellW1, W2, W3 or W4 already identified in the possible developmentscenarios (see FIG. 3); “DS1”, “DΩ” and “DS3”, which denote completingthe previously specified reservoir development scenarios; or “stop”,which denotes terminating the drilling process). Each node in thetechnological tree includes a table of the associated performancemetrics computed (e.g., oil production volume, or net present value)that correspond to the various outcomes of the reservoir development(including possible measurements at pilot/appraisal wells) that lead toor go through the node (the user may have access to these metrics viathe graphical user interface when clicking or directly touching the nodeon a screen). Although not shown in the tree above, each branch thatgoes from any “P” node of the tree (i.e., a node that implies gatheringsome additional information and proceeding down in the tree based onthat information) may also be labeled and include the data actuallymeasured (after the data measurement procedure has already taken place).

FIG. 5 depicts in flowchart form a method 500 for producing apre-calculated development manual 700, based on the developmentscenarios shown in FIG. 3. During the method 500, we evaluate theexpected value of the chosen performance metric (e.g., net present valueor oil production volume) for every implementation of each developmentscenario (i.e., at each terminal node 402 of the TT developed by thesystem 600). This evaluation is performed for every probabilitydistribution of uncertain parameters that might be obtained as a resultof appraisals or analysis of production data from production wellsdrilled as part of a scenario. Such probability distribution isrepresented by means of a set of geological realizations 504 that can beone of the sets of M reservoir models discussed above. The behavior ofeach geological realization, among the set of M reservoir models, ismodeled by means of a reservoir flow simulator 505. The evaluation ofperformance metrics 506 can be accomplished by applying an economicmodel 507 to the results of the simulations 508. Alternatively, theperformance metrics 506 can be pure physical metrics, e.g., cumulativeresource production, in which case, the economic model 507 may beomitted. Finally, the technological tree builder 502 undertakes theidentification of decisions at each internal node 403 or 404 by means ofbackward induction approach.

That is, to create the pre-calculated development manual 700, the methodproceeds upward from estimated performance metrics 506 at each leaf 402of the TT 400, computing the maximum expected value of the performancemetrics at each internal “P” node 404 and “W” node 403. The input forthe backward induction algorithm is the technological tree 400 withexpected values of performance metric mapped to each leaf 402 of thetree (each geological model that may be considered at a leaf has its ownvalue of performance metric). We assume that each leaf 402 is associatedwith one development scenario DS, but consider that one scenario mayappear at several leaves; the specific order of production wells and thenumber of appraisal wells that precedes these leaves may differ. Theoutput of the algorithm is the accumulated performance metric for eachinternal node 403 and 404 (more precisely, the metric is accumulated foreach geological model that may be considered at a node). This collectionof metrics can be used to dynamically find the path in the tree from theroot 406 to the leaf 402 with the best expected value, subject tounknown and possible research/measurement outcomes (for example, fromappraisal wells).

The backward induction algorithm proceeds upward layer-by-layer from thebottom (leaves) to the top (root). If an internal node does not provideadditional information regarding uncertain parameters (e.g., in thecurrent embodiment, a node that corresponds to the drilling of aproduction well), the metric associated with each geological model thatmay be considered at the node is the best expected value through alldescendants (where each descendant encompasses the best expected valueuntil the bottom of the tree). Otherwise, if it is possible to getadditional information (e.g., in the current embodiment, a “P” node 404that corresponds to the research performed with an appraisal well), themetric for each geological model that may be considered at the node canbe found by averaging over all submodels considered at the children ofthat node.

Thus, the initial input for the method 500 includes the following: A set501 of well arrangements (development scenarios) allowed for thereservoir; and a set of geological realizations 504. In other words, themethod 500 receives a plurality of development scenarios DS1 . . . DS3,each development scenario comprising a combination of well locations andtrajectories corresponding to appraisal wells and production wells.After also receiving the set M of geological realizations or reservoirmodels, the method 500 proceeds to modeling performance metrics 506 foreach of the development scenarios for each of the set of geologicalrealizations. Thus, values 506 of the performance metric are obtainedthrough simulations 505 for each representative geological realizationfor each well arrangement. There is an infinite number of geologicalrealizations, as geological parameters may, in general, have any valueswithin the uncertainty intervals. In certain embodiments of theinvention, we choose to simulate 505 the behavior of the reservoir for asmall number of geological realizations so that we may estimate theresults for intermediate values; the number can be selected based onexperimental design principles in light of the known parameters.Separately, the method 500 builds 502 a technological tree 400 thatdescribes the set of development scenarios. Based on the simulations505, the method 500 identifies decisions at internal nodes of thetechnological tree (see method 600, FIG. 6). Based on the decisions atinternal nodes of the technological tree, the method 500 produces apre-calculated development manual 700 that schedules optimal welldrilling sequences to accomplish the various DSs in light of evolvingfield measurements (e.g., production well flow, appraisal wellpressure).

FIG. 6, to which we now refer, depicts in greater detail theimplementation of a development planning system 600 that produces thetechnological tree 400 of FIG. 4 from the plurality of technologicallyfeasible (allowed) DSs shown in FIG. 3, according to the TT buildermethod 502. The system 600 may be facilitated by a single computer suchas the computer discussed with reference to FIG. 12, below;alternatively, the system 600 may be facilitated by the cloud computingenvironment 50. Initially, the system 600 receives the set 501 ofallowed DSs as an input 602. At the same time, the system creates theroot node 406 of the TT. If all DSs of the set 501 are fully implemented(604, Y), then the system generates one of the terminal nodes 402 forthe TT. If some DSs of the set 501 are not fully implemented (604, N),then for each DS of the set the system forms a collection 606 ofactivities (referred here as “unconditional”) whose temporaldependencies are fully satisfied. Then, the system takes theintersection of those collections to form a new collection 607 ofunconditional activities that are common for all DSs. If the collection607 is not empty (608, Y), the system marks the respective activities ascompleted at each DS and forms an updated set 609 which is passed as anew input 602 back to the system. At the same time, the collection ofcommon activities is put into the TT as a sequence of actions 403. Onthe other hand, if the collection 607 is empty (608, N), the system 600forms a set 611 of unique DS groups based on common unconditionalactivities they have. (For example, and referring also to FIG. 3, if DS1has activities “W1”, “W2” and “W4”, DS2 has activities “W1”, W3″ and“W4”, DS3 has activities “W2” and “W3”, then the set 611 would containthe following DS groups: (DS1, DS2), (DS1, DS3), (DS2, DS3).) Thisdivision of the set leads to a creation of an internal node “P” 404(FIG. 4) of the TT. Finally, each DS group is passed 613 as a new input602 to the system 600. The combined outputs 402, 403, 404, and 406 formthe complete TT 400 that is shown in FIG. 4 and that represents thetransitions between implementation schedules of each developmentscenario.

FIG. 7 shows an example of the pre-calculated development manual 700 ina form of the tabular output that could be generated as the result ofthe three-step procedure above. The table represents the order at whichproduction wells should be drilled at specified positions (“W1”, “W2”,“W3” and “W4”) based on the research outcomes (numbered as “1”, “2”, “3”and “4”) from appraisal wells (“P”). The columns in the table representtypes of actions. The fields in the cells give more details about thespecific actions. As time goes by the operator reads the cells from leftto right and performs the designated actions. For example, the “P”symbol in the leftmost cell tells the operator to start the developmentof a given region in the field with the drilling of an appraisal/pilotwell. The symbol “---” means that no further actions are required.Finally, the last column of the manual lists the names of the previouslydefined, possible development scenarios (“DS1”, “DS2” and “DS3”) thatare finally implemented as a result of the corresponding measurementsand actions. Optionally, in addition to the specific actions to beperformed, each cell of the development manual may include the expectedvalue of the performance metric associated with that cell or somerelated information, such as any production quantity that varies withtime (note that these values and information are available because allrelated computations were performed at step 505 of the method 500).Referring specifically to the numbered research outcomes after outcomeof an appraisal well, which are provided only as examples of oneimplementation of a pre-calculated development manual, these correspondto ranges or intervals of possible values for an initially uncertainparameter.

Referring to FIGS. 8-10, consider, as another example, that normalizedvalues of an uncertain parameter may vary from 0.0 to 1.0. Without anyappraisal well, the possible values that this uncertain parameter cantake are in the interval [0.0, 1.0]. With one appraisal well, assumethat the measurements associated with this appraisal well allow us todetermine that the values that this uncertain parameter can take areeither in the interval [0.0 0.5] or in the interval [0.5 1.0] (theselection of the interval depends on the measurements obtained). For twoappraisal wells, we assume that the measurements associated with thesetwo appraisal wells allows us to determine that the values that thisuncertain parameter can take are either in the interval [0.0 0.25], inthe interval [0.25 0.50], in the interval [0.50 0.75] or in the interval[0.75 1.0] (the selection of the interval depends on the measurementsobtained).

Let the dependence between the value of this uncertain parameter and theperformance metric be expressed as shown in the graph of FIG. 8 and thetable of FIG. 9. FIG. 8 shows the predicted value of a performancemetric for each development scenario (DS1, DS2 and DS3) as a function ofthe uncertain parameter. FIG. 9 shows, additionally, which of thedevelopment scenarios would maximize the performance metric for somevalues of the uncertain parameter.

Given an interval for the uncertain parameter, we could determine thebest development scenario associated with this interval by computing thecorresponding area in FIG. 8. This area can be estimated in a number ofways. In this analysis this area will be estimated by the value of theperformance metric at the center of the interval multiplied by theinterval length. Consistent with this:

If we do not plan to drill appraisal wells, we consider in the analysisone geological realization characterized by a value of the uncertainparameter equal to 0.500.

If we plan to drill one appraisal well we consider in the analysis twogeological realizations characterized by the values of the uncertainparameter equal to 0.250 and 0.750.

If we plan to drill two appraisal wells, we consider in the analysisfour geological realizations characterized by the values of theuncertain parameter equal to 0.125, 0.375, 0.625, and 0.875.

For different numbers of appraisal wells, we consult the table of FIG. 9in order to determine the best development scenario based on the maximalvalue of the performance metric in the corresponding interval.

Now, consider how a decision table, such as the table of FIG. 10, isused during the backward induction process to identify decisions at theinternal “P” nodes of a technological tree.

Consider a sub-tree with the root “W2” (that can be reached as“root”->“P”->“W2”). The leaf that is associated with developmentscenario “DS1”, which is reached as(“root”->“P”->“W2”)->“W1”->“W4”->“DS1”, has one appraisal well (“P”node) 404. That means that we need to consider two geologicalrealizations for this scenario (which are associated with the values ofthe uncertain parameter 0.250 and 0.750). Similarly, we consider thesetwo geological realizations for the leaf associated with developmentscenario “DS3”, which is reached as (“root”->“P”->“W2”)->“W3”->“DS3”.The corresponding values of performance metric are shown in columns “B”and “C” of the table shown in FIG. 10.

The development scenario “DS1” that is reached as(“root”->“P”->“W2”)->“P”->“W1”->“W4”->“DS1” has two appraisal wells.That means that we need to consider four geological realizations forthis scenario (which are associated with the values of the uncertainparameter 0.125, 0.375, 0.625 and 0.875). Similarly, we consider thesefour geological realizations for the development scenario “DS3” that isreached as (“root”->“P”->“W2”)->“P”->“W3”->“DS3”. The correspondingvalues of performance metric are shown in columns “E” and “F” of FIG.10.

In order to determine at the node “P” (that is reached as(“root”->“P”->“W2”)->“P”) the favorable development scenario for each offour geological models that may be realized, at this point we take themaximum value over development scenarios (see column “G” of FIG. 10).

Before we drill the second appraisal well, we consider two geologicalrealizations. In order to populate the tree consistent with the firstappraisal well, i.e., two intervals, we should map the four intervalsobtained after the second appraisal well to the two intervals associatedwith the first appraisal well. That can be done by averaging values ofthe performance metric for the first two and the second two intervals(see column “H”).

Finally, in order to determine the favorable development path associatedwith the level of the tree where we have two intervals as a result ofthe research/measurements performed with the first appraisal well (i.e.,at the node “W2” that is reached as “root”->“P”->“W2”), we proceed insimilar fashion as for column “G” and take the maximum value over thebranches for each of the two geological realizations (see column “I”).

The exemplary development manual shown in FIG. 7 categorizes thepotential results of each measurement “P” among four discrete outcomes(“1”-“4”) shown in the next column. The number of these outcomes dependson the data measured and may alternatively have some descriptive labels(e.g., when measuring the property “permeability” we may have “verylow”, “low”, “high”, and “very high” values of this property).Generally, the outcomes correspond to intervals of value for someuncertain parameter, as discussed above with reference to FIGS. 8-10.

Let us assume that in this example the measurement performed with theappraisal well delivered the outcome labeled as “2”. That means that thenext actions of the operator should be drilling of wells “W1” and “W4”followed by drilling of the second appraisal well. Note that thetechnological tree of FIG. 4 has branches that do not appear in thetable. This is because these branches (once the backward inductionprocess was applied) were identified as having lower performance metricthan other branches, and for that reason it does not make sense toprovide as possible actions that the operator may perform.

Upon receiving the outcome of the first appraisal measurement, theoperator may decide to eliminate the actions associated with the otheroutcomes (i.e., the first, the third, and the fourth rows, assuming theoutcome is “2”). This leaves the operator with only those instructionsthat could potentially follow further. The deletion of theabovementioned rows, again, assuming the outcome is “2”, corresponds tothe pruning of the following branches that go from the uppermost “P”node of the technological tree shown in FIG. 4: (1) branch that leads tothe “stop” terminal node, (2) branch that leads to the sub-tree with the“W2” node and (3) branch that leads to the sub-tree with the “W3” node.Note that the sub-tree after “W4”, formed by the branches starting with“W2” and “W3”, can be removed as well. (Since the manual ispre-calculated, no additional entities in the tree are created as aresult of the new data obtained from the reservoir.)

FIG. 11 shows, as a second part of the invention, how a pre-calculateddevelopment manual is implemented to dynamically adapt the developmentof an oil field. FIG. 11 depicts in flowchart form a method 1100 forutilizing the development manual 700 as developed by the method 500 ofFIG. 5. At the beginning 1101 of greenfield development, a tracker 1102of the current stage of the development is set to the root of thepre-calculated development manual 700. Based on that, an action selector(development manual implementation module) 1104 picks the very firstaction from the manual and provides 1105 this information as aninstruction to a user or development operator. If the user is instructedto drill a production well, the user performs an action on the drillingequipment 1106. The drilling affects the reservoir 1107. Once thedrilling is completed, the user informs 1108 the system of anymeasurements 1110 obtained from the reservoir. The user might beinstructed to gather information about the reservoir properties usingappraisal equipment 1109—for example, by drilling a first appraisal wellat a first appraisal location and trajectory. It should be also notedthat production well flow might inform further drilling decisions.Flow-related information from the production wells is, in general, notreadily available, in contrast to the results of the analysis performedwith appraisal wells. That means that we can consider flow informationfrom the production wells only some time later in the developmentprocess. On the other hand, some other information (e.g., downholepressure) may be immediately available. The development manual may becalculated to account for such immediate information.

In order to account for flow-related information from production wells,we may introduce some artificial nodes “Pw” that are similar to the “P”nodes. These “Pw” nodes are not associated with the drilling ofappraisal wells. The geological realizations they induce are the resultof the information from the corresponding production well that wasdrilled previously. These “Pw” nodes are added several layers down thetree at the tree level that corresponds to the moment in time when theflow-related information from the production well is considered. Thenodes may be added to each development path that lies below the nodethat represents the production well that would provide the information.

The incorporation of the flow-related information from the productionwells does not affect the process of construction of the pre-calculateddevelopment manual. The incorporation of the information from theproduction wells also does not affect the process of the usage of thepre-calculated development manual. The only difference is that thedecision at “Pw” node is made based on the information from thepreviously drilled production well, rather than from a just drilledappraisal well.

Again, the user interacts with the reservoir 1107 and enters 1108 theresults of the measurements 1110 into the system. Note that the fieldinformation 1110 can be introduced to the system as a purely manual dataentry 1108, or, if available, through some automated acquisition system.The user input interface can also be integrated with an external systemthat provides the results of reservoir measurement data analysis (e.g.,measurements performed through an appraisal well, fluid rates collectedat the production wells, etc.). The user input 1108 results in theupdate of the measurements log 1111 and updates the bookmark on thecurrent stage of the development 1102. Then, the action selector 1104again picks from the manual 700 the next action based on the currentstage 1102 and the full history of measurements 1111. Thus, for example,after drilling 1109 the first appraisal well the method 1100 mightproceed to drilling 1106 a first sequence of production wells at a firstsequence of production locations and trajectories, selected from thevarious development scenarios based on results of the first appraisalwell. Note that a “sequence” of wells may include one or more wells, ina variety of orders.

Continuing the example with reference to the exemplary developmentmanual of FIG. 7, the action selector 1104 might then instruct theoperator to drill 1109 a second appraisal well at a second appraisallocation and trajectory. Following from measurements 1110 on the secondappraisal well, the potential set of geological realizations is limited.Considering that the projected performance metric for any alloweddevelopment scenario is above a threshold value (a positive resultcorresponding to the set of geological realizations consistent with theappraisal well measurements) the action selector 1104 then mightinstruct the operator to drill 1106 a second sequence of productionwells at a second sequence of production locations and trajectories,selected from the various development scenarios based on results of thefirst and second appraisal wells.

Generally, the first appraisal location and trajectory are determined apriori while the first sequence of production locations andtrajectories, the second appraisal location and trajectory, and thesecond sequence of production locations and trajectories are selectedlater from options (the development scenarios) that were determined apriori.

When the implementation of a development scenario is completed, or whenthe projected performance metric for any allowed development scenariofalls below a threshold value (a negative result corresponding to thesubset of geological realizations consistent with the appraisal wellmeasurements), the system informs the user to stop 1112.

While operating, the method 1100 takes as preliminary input thepre-calculated development manual 700 and at each iteration the systemasks for the following intermediate input 1108: the results 1110 of thegeological research performed by means of the appraisal wells and byanalysis of production logs from the production wells that were drilledas part of the procedure previously. The method 1100 provides thefollowing output at each iteration: the order 1106 for the operator todrill a production well; the order 1109 for the operator to drill anappraisal well; or the order 1112 for the operator to drill no morewells for the reservoir.

Thus, certain embodiments of the invention provide for acomputer-implemented method that includes receiving a set of developmentscenarios, each development scenario comprising a combination of welllocations and trajectories corresponding to appraisal wells andproduction wells; building a technological tree that describes the setof development scenarios; receiving a set of geological realizations;modeling performance metrics for each of the development scenarios foreach of the set of geological realizations; based on the modeledperformance metrics, identifying internal nodes of the technologicaltree; receiving measurements from an appraisal well; and, by comparingthe measurements to the modeled performance metrics at one of theinternal nodes, selecting a sequence of production wells to be drilled.

Given the discussion thus far, it will be appreciated that, in generalterms, an exemplary method, according to an aspect of the invention,includes determining a plurality of development scenarios 501; drilling1106 or 1109 at least a first well at a first location and trajectorythat are common to the plurality of development scenarios; assessing1110 a result of the at least one first well; and drilling 1106 or 1109a first sequence of subsequent wells at a first sequence of subsequentlocations and trajectories that are common to a first subset ofdevelopment scenarios, wherein the first subset includes at least onedevelopment scenario that is selected 1104 from the plurality ofdevelopment scenarios based at least on the result of the first well,wherein the first sequence of subsequent wells includes at least onewell. This exemplary method also may include assessing a result of thefirst sequence of subsequent wells; and upon a negative result of thefirst sequence of subsequent wells, ceasing drilling 1112; or upon anypositive result of the first sequence of subsequent wells, drilling asecond sequence of subsequent wells at a second sequence of subsequentlocations and trajectories that are common to a second subset of theplurality of development scenarios, wherein the second subset includesat least one development scenario that is selected from the first subsetbased at least on the result of the first sequence of subsequent wells,wherein the second sequence of subsequent wells includes at least onewell.

Another exemplary method includes drilling 1109 a first appraisal wellat a first appraisal location and trajectory; drilling 1106 a firstsequence of production wells at a first sequence of production locationsand trajectories selected based on results of the first appraisal well;drilling 1109 a second appraisal well at a second appraisal location andtrajectory; and drilling 1106 a second sequence of production wells at asecond sequence of production locations and trajectories based onresults of the first and second appraisal wells. The first appraisallocation and trajectory are determined a priori while at least the firstsequence of production locations and trajectories and the secondsequence of production locations and trajectories are selected 1104later from a plurality of development scenarios determined a priori. Forexample, the first sequence of production locations and trajectories areselected based on comparing a first measurement on the first appraisalwell to a first plurality of intervals of a potential value of aparameter. The second appraisal location and trajectory also may beselected based on comparing a first measurement on the first appraisalwell to a first plurality of intervals of a potential value of aparameter. The second sequence of production locations and trajectoriesmay be selected based on comparing a first measurement on the firstappraisal well to a first plurality of intervals of a potential value ofa parameter and based on comparing a second measurement on the secondappraisal well to a second plurality of intervals of the potential valueof the parameter. The second plurality of intervals may include moreintervals than the first plurality of intervals.

In certain aspects, the plurality of development scenarios may becompiled in a pre-calculated development manual, and the first andfurther sequences of production locations and trajectories may beselected by comparing appraisal well measurements to intervals ofparameter values in the development manual. The development manual maybe pre-calculated according to backward induction from optimalperformance metrics for each of the development scenarios.

Certain aspects of the inventive method may also include providing asystem of distinct software modules, each of the distinct softwaremodules being embodied on a computer-readable storage medium. Thedistinct software modules may include a technological tree buildermodule, a development manual production module, and a development manualimplementation module. Pre-calculating the development manual may befacilitated by the technological tree builder module and the developmentmanual production module executing on at least one hardware processor.Selecting the first sequence of production locations and trajectoriesand the further sequences of production locations and trajectories maybe facilitated by the development manual implementation module executingon the at least one hardware processor.

Certain aspects of the inventive method may also include receiving, at atechnological tree builder module 502, a set 501 of developmentscenarios, each development scenario comprising a combination of welllocations and trajectories corresponding to appraisal wells andproduction wells; building, in the technological tree builder module502, a technological tree 400 based on the set of development scenarios;receiving, at a development manual production module, a set 504 ofgeological realizations; modeling 505, in the development manualproduction module, performance metrics for each of the developmentscenarios for each of the set of geological realizations; based on themodeled performance metrics 506, identifying internal nodes of atechnological tree 400 in the development manual production module 502;and based on the technological tree, producing a pre-calculated resourcefield development manual 700 in the development manual productionmodule. Additionally, the method may include receiving 1111, in adevelopment manual implementation module, measurements from an appraisalwell; and, by comparing the measurements to the modeled performancemetrics at one of the internal nodes, selecting 1104, in the developmentmanual implementation module, a sequence of production wells to bedrilled. The internal nodes of the technological tree may be identifiedby backward induction from optimal performance metrics for each of thedevelopment scenarios. For example, the method may include subsets ofdevelopment scenarios that correspond to intervals of a parameter value.

Other embodiments of the invention provide a computer program productthat includes a computer readable storage medium, which embodiescomputer executable instructions which when executed by a computer causethe computer to facilitate receiving, at a technological tree buildermodule 502, a set of development scenarios, each development scenariocomprising a combination of well locations and trajectoriescorresponding to appraisal wells and production wells; receiving, at adevelopment manual production module 500, a set of geologicalrealizations; modeling, in the development manual production module 500,performance metrics for each of the development scenarios for each ofthe set of geological realizations; based on the modeled performancemetrics, identifying decisions at internal nodes of a technological tree400 in the development manual production module 500; and based on thetechnological tree 400, producing a pre-calculated resource fielddevelopment manual 700 in the development manual production module. Theinstructions also may cause the computer to facilitate receiving, in adevelopment manual implementation module 1104, measurements from anappraisal well; and, by choosing a subset of geological models toproceed based on the measurements at the internal nodes “P”, selecting,in the development manual implementation module 1104, a sequence ofproduction wells to be drilled. The instructions also may cause thecomputer to facilitate identifying internal nodes of the technologicaltree by backward induction from optimal performance metrics for each ofthe development scenarios. For example, the instructions may cause thecomputer to facilitate identifying subsets of development scenarios thatcorrespond to intervals of a parameter value.

Other embodiments of the invention provide an apparatus that includes amemory and at least one processor. The processor is operative tofacilitate receiving, at a technological tree builder module 502, a set501 of development scenarios, each development scenario comprising acombination of well locations and trajectories corresponding toappraisal wells and production wells; building, in the technologicaltree builder module 502, a technological tree 400 based on the set 501of development scenarios; receiving, at a development manual productionmodule 500, a set of geological realizations 504; modeling, in thedevelopment manual production module, performance metrics for each ofthe development scenarios for each of the set of geologicalrealizations; based on the modeled performance metrics, identifyingdecisions at internal nodes 403, 404 of the technological tree 400 inthe development manual production module; and based on the technologicaltree 400, producing a pre-calculated resource field development manual700 in the development manual production module 500. The processor maybe further operative to facilitate receiving, in a development manualimplementation module 1104, measurements from an appraisal well; and bychoosing a subset of geological models to proceed based on themeasurements at one of the internal nodes, selecting, in the developmentmanual implementation module, a sequence of production wells to bedrilled. Additionally, the processor may be operative to facilitatepopulating the decision tables in internal nodes of the technologicaltree by backward induction from optimal performance metrics for each ofthe development scenarios. Moreover, the processor may be operative tofacilitate identifying subsets of development scenarios that correspondto intervals of a parameter value.

As will be appreciated by one skilled in the art, aspects of the presentinvention may be embodied as a system, method or computer programproduct. Accordingly, aspects of the present invention may take the formof an entirely hardware embodiment, an entirely software embodiment(including firmware, resident software, micro-code, etc.) or anembodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” “module” or “system.”Furthermore, aspects of the present invention may take the form of acomputer program product embodied in one or more computer readablemedium(s) having computer readable program code embodied thereon.

One or more embodiments of the invention, or elements thereof, can beimplemented in the form of an apparatus including a memory and at leastone processor that is coupled to the memory and operative to performexemplary method steps.

One or more embodiments can make use of software running on a generalpurpose computer or workstation. With reference to FIG. 12, such animplementation might employ, for example, a processor 1202, a memory1204, and an input/output interface formed, for example, by a display1206 and a keyboard 1208. The term “processor” as used herein isintended to include any processing device, such as, for example, onethat includes a CPU (central processing unit) and/or other forms ofprocessing circuitry. Further, the term “processor” may refer to morethan one individual processor. The term “memory” is intended to includememory associated with a processor or CPU, such as, for example, RAM(random access memory), ROM (read only memory), a fixed memory device(for example, hard drive), a removable memory device (for example,diskette), a flash memory and the like. In addition, the phrase“input/output interface” as used herein, is intended to include, forexample, one or more mechanisms for inputting data to the processingunit (for example, mouse), and one or more mechanisms for providingresults associated with the processing unit (for example, printer). Theprocessor 1202, memory 1204, and input/output interface such as display1206 and keyboard 1208 can be interconnected, for example, via bus 1210as part of a data processing unit 1212. Suitable interconnections, forexample via bus 1210, can also be provided to a network interface 1214,such as a network card, which can be provided to interface with acomputer network, and to a media interface 1216, such as a diskette orCD-ROM drive, which can be provided to interface with media 1218.

Accordingly, computer software including instructions or code forperforming the methodologies of the invention, as described herein, maybe stored in one or more of the associated memory devices (for example,ROM, fixed or removable memory) and, when ready to be utilized, loadedin part or in whole (for example, into RAM) and implemented by a CPU.Such software could include, but is not limited to, firmware, residentsoftware, microcode, and the like.

A data processing system suitable for storing and/or executing programcode will include at least one processor 1202 coupled directly orindirectly to memory elements 1204 through a system bus 1210. The memoryelements can include local memory employed during actual implementationof the program code, bulk storage, and cache memories which providetemporary storage of at least some program code in order to reduce thenumber of times code must be retrieved from bulk storage duringimplementation.

Input/output or I/O devices (including but not limited to keyboards1208, displays 1206, pointing devices, and the like) can be coupled tothe system either directly (such as via bus 1210) or through interveningI/O controllers (omitted for clarity).

Network adapters such as network interface 1214 may also be coupled tothe system to enable the data processing system to become coupled toother data processing systems or remote printers or storage devicesthrough intervening private or public networks. Modems, cable modem andEthernet cards are just a few of the currently available types ofnetwork adapters.

As used herein, including the claims, a “server” includes a physicaldata processing system (for example, system 1212 as shown in FIG. 12)running a server program. It will be understood that such a physicalserver may or may not include a di splay and keyboard.

As noted, aspects of the present invention may take the form of acomputer program product embodied in one or more computer readablemedium(s) having computer readable program code embodied thereon. Anycombination of one or more computer readable medium(s) may be utilized.The computer readable medium may be a computer readable signal medium ora computer readable storage medium. A computer readable storage mediummay be, for example, but not limited to, an electronic, magnetic,optical, electromagnetic, infrared, or semiconductor system, apparatus,or device, or any suitable combination of the foregoing. Media block1218 is a non-limiting example. More specific examples (a non-exhaustivelist) of the computer readable storage medium would include thefollowing: an electrical connection having one or more wires, a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), an optical fiber, a portable compact disc read-onlymemory (CD-ROM), an optical storage device, a magnetic storage device,or any suitable combination of the foregoing. In the context of thisdocument, a computer readable storage medium may be any tangible mediumthat can contain, or store a program for use by or in connection with aninstruction execution system, apparatus, or device.

It should be noted that any of the methods described herein can includean additional step of providing a system comprising distinct softwaremodules embodied on a computer readable storage medium; the modules caninclude, for example, any or all of the appropriate elements depicted inthe block diagrams and/or described herein; by way of example and notlimitation, any one, some or all of the modules/blocks and orsub-modules/sub-blocks described.

One example of user interface that could be employed in some cases ishypertext markup language (HTML) code served out by a server or thelike, to a browser of a computing device of a user. The HTML is parsedby the browser on the user's computing device to create a graphical userinterface (GUI).

It should be noted that any of the methods described herein can includean additional step of providing a system comprising distinct softwaremodules embodied on a computer readable storage medium; the modules caninclude, for example, any or all of the elements depicted in the blockdiagrams and/or described herein; by way of example and not limitation,a technological tree builder module, a development manual productionmodule, and a development manual implementation module. The method stepscan then be carried out using the distinct software modules and/orsub-modules of the system, as described above, executing on one or morehardware processors 1202. For example, the technological tree buildermodule 502 facilitates the steps 602-613 of building the technologicaltree 400. The development manual production module 500 facilitates thesteps 501-508 of producing the development manual 700 from thetechnological tree 400. The development manual implementation module1100 facilitates the steps 1101-1112 of implementing the developmentmanual 700 on a reservoir 1107. Further, a computer program product caninclude a computer-readable storage medium with code adapted to beimplemented to carry out one or more method steps described herein,including the provision of the system with the distinct softwaremodules.

In any case, it should be understood that the components illustratedherein may be implemented in various forms of hardware, software, orcombinations thereof; for example, application specific integratedcircuit(s) (ASICS), functional circuitry, one or more appropriatelyprogrammed general purpose digital computers with associated memory, andthe like. Given the teachings of the invention provided herein, one ofordinary skill in the related art will be able to contemplate otherimplementations of the components of the invention.

Exemplary System and Article of Manufacture Details

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below are intended toinclude any structure, material, or act for performing the function incombination with other claimed elements as specifically claimed. Thedescription of the present invention has been presented for purposes ofillustration and description, but is not intended to be exhaustive orlimited to the invention in the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the artwithout departing from the scope and spirit of the invention. Theembodiment was chosen and described in order to best explain theprinciples of the invention and the practical application, and to enableothers of ordinary skill in the art to understand the invention forvarious embodiments with various modifications as are suited to theparticular use contemplated.

1. A method for developing a resource field, comprising: determining a plurality of development scenarios; drilling at least a first well at a first location and trajectory that are common to the plurality of development scenarios; assessing a result of the at least one first well; and drilling a first sequence of subsequent wells at a first sequence of subsequent locations and trajectories that are common to a first subset of development scenarios, wherein the first subset includes at least one development scenario that is selected from the plurality of development scenarios based at least on the result of the first well, wherein the first sequence of subsequent wells includes at least one well.
 2. The method of claim 1 further comprising: assessing a result of the first sequence of subsequent wells; and upon a negative result of the first sequence of subsequent wells, ceasing drilling; or upon any positive result of the first sequence of subsequent wells, drilling a second sequence of subsequent wells at a second sequence of subsequent locations and trajectories that are common to a second subset of the plurality of development scenarios, wherein the second subset includes at least one development scenario that is selected from the first subset based at least on the result of the first sequence of subsequent wells, wherein the second sequence of subsequent wells includes at least one well.
 3. The method of claim 2 wherein the second sequence of subsequent locations and trajectories are selected based on comparing a measurement on the first sequence of subsequent wells to a plurality of intervals of a potential value of a parameter.
 4. The method of claim 2 wherein the second sequence of subsequent locations and trajectories are selected based on comparing a first measurement on the first well to a first plurality of intervals of a potential value of a parameter and based on comparing a second measurement on the first sequence of subsequent wells to a second plurality of intervals of the potential value of the parameter, wherein the second plurality includes more intervals than the first plurality.
 5. The method of claim 1 wherein the first sequence of subsequent locations and trajectories are selected based on comparing a measurement on the first well to a plurality of intervals of a potential value of a parameter.
 6. The method of claim 1 wherein the plurality of development scenarios are compiled in a pre-calculated development manual, and the first subset of development scenarios are selected by comparing at least one result of the first well to intervals of at least one parameter in the development manual.
 7. The method of claim 6 wherein the development manual is pre-calculated according to backward induction based on optimal performance metrics for each of the plurality of development scenarios.
 8. The method of claim 6, further comprising providing a system, wherein the system comprises distinct software modules, each of the distinct software modules being embodied on a computer-readable storage medium, and wherein the distinct software modules comprise a technological tree builder module, a development manual production module, and a development manual implementation module; wherein: pre-calculating the development manual is facilitated by said technological tree builder module and said development manual production module executing on at least one hardware processor; and selecting the first subset of development scenarios is facilitated by said development manual implementation module executing on said at least one hardware processor.
 9. The method of claim 1 further comprising: receiving, at a technological tree builder module, a set of development scenarios, each development scenario comprising a combination of well locations and trajectories corresponding to appraisal wells and production wells; building, in the technological tree builder module, a technological tree based on the set of development scenarios; receiving, at a development manual production module, a set of geological realizations; modeling, in the development manual production module, performance metrics for each of the development scenarios for each of the set of geological realizations; based on the modeled performance metrics, identifying decisions at internal nodes of a technological tree in the development manual production module; and based on the technological tree, producing a pre-calculated resource field development manual in the development manual production module.
 10. The method of claim 9 further comprising: receiving, in a development manual implementation module, at least one result from a first well; choosing at one of the internal nodes a subset of geological models to proceed with based on the at least one result; and selecting, in the development manual implementation module based on the subset of geological models, a first sequence of subsequent wells to be drilled.
 11. The method of claim 9 wherein populating internal nodes of the technological tree is accomplished from optimal performance metrics for each of the development scenarios.
 12. The method of claim 11 further comprising populating a first plurality of internal nodes corresponding to appraisal well measurements and populating a second plurality of internal nodes corresponding to production well measurements.
 13. A computer program product comprising a computer readable storage medium embodying computer executable instructions which when executed by a computer cause the computer to facilitate the method of: receiving, at a technological tree builder module, a set of development scenarios, each development scenario comprising a combination of well locations and trajectories corresponding to appraisal wells and production wells; building, in the technological tree builder module, a technological tree based on the set of development scenarios; receiving, at a development manual production module, a set of geological realizations; modeling, in the development manual production module, performance metrics for each of the development scenarios for each of the set of geological realizations; based on the modeled performance metrics, identifying internal nodes of a technological tree in the development manual production module; and based on the technological tree, producing a pre-calculated resource field development manual in the development manual production module.
 14. The product of claim 13 further comprising computer executable instructions which when executed by a computer cause the computer to facilitate: receiving, in a development manual implementation module, at least one result from a first well; and choosing at one of the internal nodes a subset of geological models to proceed with based on the at least one result; and selecting, in the development manual implementation module based on the subset of geological models, a first sequence of subsequent wells to be drilled.
 15. The product of claim 13 further comprising computer executable instructions which when executed by a computer cause the computer to facilitate identifying internal nodes of the technological tree from optimal performance metrics for each of the development scenarios.
 16. The product of claim 15 further comprising computer executable instructions which when executed by a computer cause the computer to populate a first plurality of internal nodes corresponding to appraisal well measurements and to populate a second plurality of internal nodes corresponding to production well measurements.
 17. An apparatus comprising: a memory; and at least one processor operative to facilitate: receiving, at a technological tree builder module, a set of development scenarios, each development scenario comprising a combination of well locations and trajectories corresponding to appraisal wells and production wells; building, in the technological tree builder module, a technological tree based on the set of development scenarios; receiving, at a development manual production module, a set of geological realizations; modeling, in the development manual production module, performance metrics for each of the development scenarios for each of the set of geological realizations; based on the modeled performance metrics, identifying decisions at internal nodes of the technological tree in the development manual production module; and based on the technological tree, producing a pre-calculated resource field development manual in the development manual production module.
 18. The apparatus of claim 17 wherein the processor is further operative to facilitate: receiving, in a development manual implementation module, measurements from an appraisal well; and choosing at one of the internal nodes a subset of geological models to proceed with based on the at least one result; and selecting, in the development manual implementation module based on the subset of geological models, a first sequence of subsequent wells to be drilled.
 19. The apparatus of claim 17 wherein the processor is further operative to facilitate identifying internal nodes of the technological tree from optimal performance metrics for each of the development scenarios.
 20. The apparatus of claim 19 wherein the processor is further operative to facilitate populating a first plurality of internal nodes corresponding to appraisal well measurements and populating a second plurality of internal nodes corresponding to production well measurements. 